Find research datasets worth reusing

opencc-by-4.0Feb 2023View details →

A Dataset for Lateral Load Capacities of Large Scale Monopiles

The dataset is used for training a hybrid neural network and is generated using Finite Element Modeling. The presented dataset contains the lateral response (kN) of the monopile at 0.5 and 1 degree of rotation along with the monopile's length (m), the moment of inertia (m4), and load eccentricity (m). The dataset also contains the values of depth (m) and its corresponding cone resistance (qc: kPa) obtained from the CPT test.

opencc-by-4.0Feb 2023View details →

supplementary to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" , 2D wind forcing

This is a supplementary material to article "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" ( unpublished at the publication date of this dataset) It contains the 2D wind forcing for Crocus-SnowPappus simulations on the Grandes Rousses test zone. It was generated using DEVINE wind downscaling method ( Le Toumelin et al., 2022 )

opencc-by-4.0Mar 2023View details →

Data from "Enhanced radiative forcing from aerosol-cloud interactions due to large-scale circulation adjustments" by Guy Dagan, Netta Yeheskel and Andrew I. L. Williams.

This is the data presented in "Enhanced radiative forcing from aerosol-cloud interactions due to large-scale circulation adjustments" by Guy Dagan, Netta Yeheskel and Andrew I. L. Williams.   Please read the README file for explanations about the data.

opencc-by-4.0Jan 2023View details →

Defectors: A Large Scale Python Dataset for Defect Prediction

Defect prediction has been a major research problem in the software engineering domain for the last five decades. In recent years, large deep-learning models have shifted the performance of software engineering tasks to new limits and are gaining usage in defect prediction. However, these defect prediction models are often limited by the quality of their datasets, which are not large or diverse enough. In this paper, we present Defectors, a large dataset for both line-level and just-in-time defect prediction. Defectors consist of $\approx$ 213K source code files ($\approx$ 93K defective and $\approx$ 120K defect-free files) from 25 popular python projects from various domains and organizations. These projects come from a diverse set of domains including machine learning, automation, and internet-of-things. Such a scale and diversity make Defectors a suitable dataset for deep learning models, especially transformer models that require large and diverse datasets to effectively generalize defect-inducing patterns to predict future defects. <table> <caption>Dataset Description</caption> <tbody> <tr> <td>File Name</td> <td>Description</td> </tr> <tr> <td>defectors.zip</td> <td>The original Dataset. Find its description in Section II of the paper.</td> </tr> <tr> <td>bug_inducing_commits.zip</td> <td>Each yaml file contains a map of bugfix commits to bug-inducing commits.</td> </tr> <tr> <td>filtered_bug_inducing_commits.yaml</td> <td>A map in structure {repo_name: {bug_inducing_commits: [list of python files in the commit]}}. This file only contains the bug-inducing commits that match the filtering criteria from Section III.D.</td> </tr> <tr> <td>repo_links.yaml</td> <td>Links to the repositories we used to construct the dataset.</td> </tr> </tbody> </table>

opencc-by-4.0Apr 2023View details →

Large-scale saliva pooling as a screening strategy to control transmission_raw data

This dataset include the raw data of our experience after building a bespoke laboratory to control critical areas by pooling samples of saliva. From August 2020 to February 2022; 928,528 individual self-samples of saliva were processed in 52,580 pools, 4,935 of which were positive and helped us detect 5,806 nonsymptomatic individuals.  The dataset was collected directly from the laboratory information system and was processed to delete the columns with sensitive information. The Dataset was charged as XLSX file and only need a compatible software. To facilitate the understanding of the data set, which uses the Galician language and an internal nomenclature of our laboratory, we include a sheet named "description" and a README file in which it defines the terms used and their equivalence with those used in the article.

openother-openApr 2023View details →

Data from: Chilean bee diversity: Contrasting patterns of species and phylogenetic turnover along a large-scale ecological gradient

Title of dataset Data from: Chilean bee diversity: Contrasting patterns of species and phylogenetic turnover along a large-scale ecological gradient Authors of dataset Leon Marshall1,2, John S. Ascher3, Cristian Villagra4, Amaury Beaugendre1, Valentina Herrera4, Patricia Henríquez-Piskulich4, Alejandro Vera5, Nicolas J. Vereecken1 <ol> <li>Agroecology Lab, Université libre de Bruxelles (ULB), Boulevard du Triomphe CP 264/2, B 1050 Brussels, Belgium</li> <li>Naturalis Biodiversity Center, Darwinweg 2, 2333 CR Leiden, The Netherlands</li> <li>Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543, Singapore</li> <li>Instituto de Entomología, Universidad Metropolitana de Ciencias de la Educación, Santiago, Región Metropolitana, Chile</li> <li>Departamento de Biología, Universidad Metropolitana de Ciencias de la Educación, Santiago, Región Metropolitana, Chile</li> </ol> Abstract Chile's isolation and varied climates have driven the evolution of a unique biodiversity with a high degree of endemism. As a result, Chile encompasses diverse environments, including the Mediterranean-type ecosystem, a global biodiversity hotspot. These environments are currently threatened by anthropogenic land use change impacting the integrity of local biomes and associated species. This area is the most intensively sampled of the country with high endemicity of native bee species. Characterising habitat requirements of bees is a pressing priority to safeguard these insects and the ecosystem services they provide. We investigated broad-scale patterns of bee (Hymenoptera: Apoidea: Anthophila) diversity using newly accessible expert-validated datasets comprising digitized specimen records from Chilean and US collections, and novel expert-validated type specimen data for the bees of Chile. We used a generalised dissimilarity modelling (GDM) approach to explore both compositional and phylogenetic β-diversity patterns across latitudinal, altitudinal, climate and habitat gradients in well-sampled bee assemblages in Central Chile. Using the GDM measures of increasing compositional and environmental dissimilarity we categorised and compared the most important drivers of these patterns and used them to classify 'wild bee ecoregions' (WBE) representing unique assemblages. Turnover of bee assemblages was explained primarily by latitudinal variation (proxy for climate) from south to north in Chile. However, temperature variations, precipitation and the presence of bare soil also significantly explained turnover in bee assemblages. In comparison, we observed less turnover in phylogenetic biodiversity corresponding to spatial gradients. We identified six de novo ecoregions (WBE), all with distinct taxa, endemic lineages, and representative species. The WBE represent distinct spatial classifications but have similarities to existing biogeographical classifications, ecosystems and bioclimatic zones. This approach establishes the baseline needed to prioritise bee species conservation efforts across this global biodiversity hotspot. We discuss the novelty of this classification considering previous biogeographical characterisations and their relevance in assessing conservation priorities for bee conservation. We argue that Chile's WBE highlight areas in need of funding for bee species surveys and description, distribution mapping and strengthening of conservation policies. Usage notes The dataset contains species occurrence data of chilean bees aggregated to a 5 x 5 km grid shapefile. The shapefile of the grid and the raster mask of the Central Chilean study area are also included. Finally, a database of type specimen data used to supplement the dataset is included here.  The code for the analysis can be found at: <a href="https://github.com/lmar116/ChileanBeeDiversity">https://github.com/lmar116/ChileanBeeDiversity</a>. Shapefiles, rasters, CSV files and code were all loaded and analyzed using R statistics software.  Four files are included: <ol> <li>Marshall-et-al-2023_Ecosphere_DataTable_bee_grid: contains all species occurrence data used in GDM analysis, Grid column refers to cl.5km.shp.</li> <li>cl.5km.shp (and associated files): 5 x 5 km grid shapefile of the Central Chilean study area</li> <li>chile.mask.tif: raster outline of the Central Chilean study area</li> <li>Marshall-et-al-2023_Ecosphere_CentralChileTypeSpecimens.xlsx: contains type specimen data used to supplement species occurrence dataset.</li> </ol>

opencc-by-4.0Apr 2023View details →

MMpedia: A Large-scale Multi-modal Knowledge Graph

List of files: <ul> <li>entity2image.json: The entity to map images file</li> <li>MMpedia_triples.ttl: The triples file</li> <li>EntlistXX.tar: The image file</li> </ul> MMpedia dataset is split into 132 subsets and each subset is compressed into a <code>.tar</code> file. After unziping files under the folder "MMpedia", the data structure are as following: <pre><code>|-MMpedia |-Entitylist1 |-Entity1 |-1.jpg |-2.jpg |-3.jpg ... |-Entity2 |-Entity3 ... |-Entitylist2 |-Entitylist3</code></pre> For example, the path <code>MMpedia/Entlist141/Bart Tanski/Bart Tanski+1.jpg</code> means the image corresponding to the entity "Bart Tanski" Other image files can be found in following URLs: <a href="https://zenodo.org/record/7854781#.ZEU7Uc7iu38">MMpedia2 | Zenodo</a> <a href="https://zenodo.org/record/7855010">MMpedia3 | Zenodo</a> <a href="https://zenodo.org/record/7855226">MMpedia4 | Zenodo</a>  For more details, please refer to <a href="https://github.com/Delicate2000/MMpedia">Delicate2000/MMpedia (github.com)</a>

opencc-by-4.0Nov 2022View details →

READ: Large-Scale Neural Scene Rendering for \\ Autonomous Driving

With the development of advanced driver assistance systems~(ADAS) and autonomous vehicles, conducting experiments in various scenarios becomes an urgent need. Although having been capable of synthesizing photo-realistic street scenes, conventional image-to-image translation methods cannot produce coherent scenes due to the lack of 3D information. In this paper, a large-scale neural rendering method is proposed to synthesize the autonomous driving scene~(READ), which makes it possible to generate large-scale driving scenes in real time on a PC through a variety of sampling schemes. In order to effectively represent driving scenarios, we propose an ω rendering network to learn neural descriptors from sparse point clouds. Our model can not only synthesize photo-realistic driving scenes but also stitch and edit them. The promising experimental results show that our model performs well in large-scale driving scenarios.   Source Code: https://github.com/JOP-Lee/READ

opencc-by-4.0May 2023View details →

Experimental dataset on a large-scale urban drainage physical facility

The present dataset contains the results from the test carried out at a large-scale urban drainage facility located in the Hydraulics Laboratory of the Centre of Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain) within the scope of the project SATURNO - Early warning against pluvial flooding in urban areas [PID2020-118368RB-I00]. The main goal of the project SATURNO is to establish a robust methodology for the development and implementation of operational Early Warning System (EWS) for pluvial flood risk in urban areas. The experimental facility represents a T-intersection street of 100 m2 linked to a sewer system, and it is equipped with a rainfall simulator able to generate spatially homogeneous rainfall intensities. The dataset includes the results of experiments on roofs, street surfaces, inlets, manholes and the outfall of the drainage system as well as all products obtained during the tests. The dataset is structured in the following items: <ul> <li>01_Physical_model_description: Full description of the urban drainage installation.</li> <li>02_Geometries: Geometry of streets, roofs, and drainage network ready for import into numerical.</li> <li>03_Rain_intensity_maps: Rainfall maps of the intensities generated with the rainfall simulator in the experiments.</li> <li>04_Digital_Elevation_Models: Digital Terrain Models of the street surface and roofs.</li> <li>05_Experimental_procedure: Full description of the experimental procedure, equipment, measuring points, results, and structure of the database.</li> <li>06_ Hydraulic_tests_database: Database with post-processed experimental results ready for use. Results of flow rates of the 4 roofs, the 4 inlets, the 4 manholes, the grate and the outfall and the depths of the 9 surface points are presented. A file with additional data on the measuring points is also included.</li> <li>07_Supplementary_material: QGIS project with the products obtained.</li> <li>08_Multimedia: Photos and videos of the platform and experiments.</li> </ul> The roofs results have been used in Sañudo et al. (2022) to assess three different numerical implementations to model rainfall-runoff transformation on roofs [DOI: <a href="https://doi.org/10.1002/hyp.14588">https://doi.org/10.1002/hyp.14588</a>] This study was received financial support from the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) within the project “SATURNO: Early warning against pluvial flooding in urban areas” (PID2020-118368RB-I00).

opencc-by-4.0May 2023View details →

Exact large-scale fluctuations of the phase field in the sine-Gordon model

Raw data and Mathematica Notebooks for the thermodynamics and phase correlations in the sine-Gordon model It can be found: <ol> <li>A transfer matrix code for equilibrium correlation functions.</li> <li>A solver for the classical Thermodynamic Bethe Ansatz and the correlation functions of the phase field.</li> <li>A solver of the Thermodynamic Bethe Ansatz of the quantum sine-Gordon at the reflectionless points, and the computation of cumulants of the phase field.</li> <li>Monte Carlo data presented in the paper: cumulants of the phase field at unequal times on homogeneous thermal background and phase correlation on the inhomogeneous background mimicking the tunnel-coupled experiments.</li> <li>Mathematica notebooks that read the data and produce the figures shown in the paper.</li> </ol>

opencc-by-4.0Dec 2022View details →

Agroforestry-based community forestry as a large-scale strategy to reforest agricultural encroachment areas in Myanmar: ambition vs. local reality

Abstract:  Context:  The high rate of deforestation in Myanmar is mainly due to agricultural expansion. One task of the Forest Department is to increase tree cover in the encroaching farmland by establishing large-scale agroforestry-based community forests (ACFs). Aim:  The objectives of this study were to analyze the adoption and performance of the ACFs in the agricultural encroachment areas in the Bago-Yoma region, Myanmar; and to provide recommendations to enhance the adoption of ACFs by farmers. Methods:  We inventoried 42 sample plots and surveyed 291 farmers. Survey responses were analyzed by binary logistic regression, one-way ANOVA, and non-parametric correlation tests to evaluate factors influencing the adoption of ACFs. Stand characteristics were calculated from the inventory data to evaluate the performance of ACFs. Results:  Our results show that farmer participation in ACFs was lower than stated in the registry of the Forest Department. Farmers practiced four different agroforestry designs in ACFs with different outcomes. The Forest Department strongly determined tree species and planting designs, farmers’ perception and participation in ACFs. Farmland size, unclear and insufficient information on ACFs, and a negative perception of raising trees in crop fields were the major factors limiting the adoption rates of ACFs.  Conclusion:  We recommend capacity building for farmers and Forest Department staff and raising awareness about the benefits of planting designs and trees on farmland. A stronger consideration of farmers’ preferences for design and species selection could increase their motivation to adopt ACFs and improve the long-term sustainability of ACFs.

Throughfall exclusion and fertilization effects on tropical dry forest tree plantations, a large-scale experiment

Across tropical ecosystems, global environmental change is causing drier climatic conditions and increased nutrient deposition. Such changes represent large uncertainties due to unknown interactions between drought and nutrient availability in controlling ecosystem net primary productivity (NPP). Using a large-scale manipulative experiment, we studied for 4 years whether nutrient availability affects the individual and integrated responses of aboveground and belowground ecosystem processes to throughfall exclusion in 30-year-old mixed plantations of tropical dry forest tree species in Guanacaste, Costa Rica. We used a factorial design with four treatments: control, fertilization (F), drought (D), and drought + fertilization (D + F). While we found that a 13 %–15 % reduction in soil moisture only led to weak effects in the studied ecosystem processes, NPP increased as a function of F and D + F. The relative contribution of each biomass flux to NPP varied depending on the treatment, with woody biomass being more important for F and root biomass for D + F and D. Moreover, the F treatment showed modest increases in maximum canopy cover. Plant functional type (i.e., N fixation or deciduousness) and not the experimental manipulations was the main source of variation in tree growth. Belowground processes also responded to experimental treatments, as we found a decrease in nodulation for F plots and an increase in microbial carbon use efficiency 25 for F and D plots. Our results emphasize that nutrient availability, more so than modest reductions in soil moisture, limits ecosystem processes in tropical dry forests and that soil fertility interactions with other aspects of drought intensity (e.g., vapor pressure deficit) are yet to be explored.

Large-scale restoration of species-rich dry grasslands on arable land: Environmental filtering drives successful species establishment over a period of 10 years

Sowing of regionally specific seed mixtures on former arable land is increasingly used to restore species-rich grasslands, but it often faces important obstacles in environmental conditions and colonisation from preserved surrounding grasslands. Long-term landscape scale studies, which explore the processes governing plant establishment from seed mixtures and later colonisation from the surrounding landscape are scarce. We studied the species and functional trait composition of 32 grasslands restored 1–11 years before the first sampling by sowing regional seed mixtures in the White Carpathian Mts (SE Czech Republic). We compared them with 23 well-preserved permanent grasslands in their surroundings. In each grassland we estimated plant species cover in three plots of 25 m2, in restored grasslands in 2009, 2014 and 2019, in permanent grasslands in 2009. The species composition of the restored grasslands converged towards the permanent grasslands due to expansion of dry grassland species and retreat of mesic grassland and weed species. The majority (60–71%) of the vegetation cover of restored grasslands was formed by sown species, while the species number was mainly determined by colonising unsown species (61–63%). The species number of restored grasslands remained lower than that in permanent grasslands. Functional trait composition (Community Weighted Mean) of the sown seed mixtures, permanent grasslands and restored grasslands overlapped in all three samplings. With increasing grassland age, species with resource-retaining traits of low specific leaf area and high leaf dry matter content, lower stature, higher seed mass, and lower capacity for clonal reproduction expanded. Functional trait diversity of the plots was mostly lower than expected by null model randomisations of community, which indicates strong environmental filtering. Comparison of newly colonising species and extinct species indicated that mainly species with traits similar to the rest of the community are able to colonise the grasslands successfully. Synthesis and applications. Sowing of regionally specific seed mixtures was successful and demonstrated to be a fast way of grassland restoration, particularly in terms of functional trait composition. The resulting species diversity depended on the colonisation processes, which are controlled by the functional composition of the local communities.

Large-scale changes in macrobenthic biodiversity driven by mangrove afforestation

<ol> <li>Large-scale anthropogenic mangroves have been constructed in coastal regions worldwide, but our understanding of their ecological effects is limited. In particular, the question of whether and how anthropogenic mangroves influence biodiversity patterns remains elusive.</li> <li>Here, we investigated the influence of large-scale anthropogenic mangroves on biodiversity patterns of mangrove macrobenthos. Specifically, we measure and seek to explain differences in species richness, abundance, assemblage composition, and distance-decay effect before and after the construction of anthropogenic mangroves.</li> <li>We surveyed assemblages of gastropod, bivalve and crab species over a wide latitudinal extent (24–28°N) in subtropical China. For each, we calculated species richness, abundance, assemblage composition, and distance-decay relationship before and after the construction of anthropogenic mangroves.</li> <li> After the large-scale anthropogenic mangroves, we found species richness of gastropods, bivalves and crabs increased by 23.81%, 100% and 20%, respectively. The distance-decay effects of gastropods and bivalves decreased by 25% and 91.43%, while that of crabs remained virtually unchanged, indicating that large-scale monospecific planting changed spatial processes of macrobenthos (e.g., dispersal limitation). With mangrove plantation, compositional similarity of crab and bivalve assemblages increased by 28.57% and 38.46%, suggesting that large-scale monospecific planting exacerbates biotic homogenization. Altogether, these results indicate that large-scale anthropogenic habitats increase the diversity of mangrove macrobenthos and change taxonomic compositions by reducing distance-decay effects. </li> <li> Synthesis and applications. We emphasize that afforestation of coastal wetlands can drive major changes in benthonic communities. Monitoring and assessing the ecological effects of the anthropogenic habitats for the presence of functional faunas will be important in determining the future coastal restoration and maintaining economic aquaculture. Quantifying those effects in terms of regional biodiversity composition enables management decisions about habitat restoration to be based upon macro-evidence rather than wishful thinking or untested intuition even or a one-sided local perspective. </li> </ol>

Large-scale exploration of nitrogen utilization efficiency in Asia region for rice crop: variation patterns and determinants

Improving rice nitrogen utilization efficiency (NUtE) is imperative to maximizing future food productivity while minimizing environmental threats, yet knowledge of its variation and the underlying regulatory factors is still lacking. Here, we integrated a dataset with 21,571 data compiled by available data from peer-reviewed literature and a large-scale field survey to address this knowledge gap. The overall results revealed great variations in rice NUtE, which were mainly associated with human activities, climate conditions and rice variety. Specifically, N supply rate, temperature and precipitation were the foremost determinants of rice NUtE, and NUtE responses to climatic change differed among rice varieties. Further prediction highlighted the improved rice NUtE with the increasing latitude or longitude. The indica and hybrid rice exhibited higher NUtE in low-latitude regions compared to japonica and inbred rice, respectively. Collectively, our results evaluated the primary drivers of rice NUtE variations and predicted the geographical responses of NUtE in different varieties. Linking the global variations in rice NUtE with environmental factors and geographical adaptability provides valuable agronomic and ecological insights into the regulation of rice NUtE.

opencc-by-4.0Jul 2023View details →

1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 3

PART 1 IS FOUND AT  https://doi.org/10.5281/zenodo.8118023 PART 2 IS FOUND AT  https://doi.org/10.5281/zenodo.8119090   ===================================================================================================== Author        :     L. Bucciantini Date         :    05/07/2023 Laboratory    :    CNRS-LPC2E, Orléans (France) ===================================================================================================== Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will find in it. In case you need help with using the dataset, or if you are interested in mutual impedance experiments, do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu) ===================================================================================================== Topic: This dataset contains the outputs of numerical simulations performed to assess the impact of plasma inhomogeneities on the diagnostic performance of mutual impedance experiments. Numerical model: The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson system of equations. The scheme used to solve the model is the one developed by Mangeney et al. (2002),  A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071). The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind, Journal of Geophysical Research (Space Physics), 115, 6106 (2010) ----------------------------------------------------------------------------------------------------- What is inside the dataset: The dataset is composed of 7 different mutual impedance measurements, each corresponding to one directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity. Each directory contains a number of folders. Each folder corresponds to the emission of a signal at different frequency. ----------------------------------------------------------------------------------------------------- List of directories: (Note : each directory corresponds to one mutual impedance measurement) L        :    These outputs correspond to one mutual impedance measurement in                 small antenna emission amplitude, which corresponds to a linear                 plasma response to the emission. s_xx     :    Each of these outputs corresponds to one mutual impedance measurement in correspondance of         a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna          ----------------------------------------------------------------------------------------------------- List of folders inside the directories: Folders begin with the name "000" and have increasing index. Inside the same directory, each folder represents a different simulation used to build the same mutual impedance measurement. ------------------------------------------------------------------------------------------------------ List of files inside the folders: density_e.npz        :    electron density inside the box, in function of time (tempo) density_p.npz        :    ion density inside the box, in function of time (tempo) E.npz            :    electric field in the box, in function of time (tempo) qrho.npz        :    electric potential in the box, in function of time (tempo) qrho_imposed.npz    :    electric charge imposed at the emitting antennas, in function of time (tempo) tempo.npz        :    time-vector for density, electric field, electric potential and charge vectors TEST_Luca.dat        :    parameters describing the characteristics of the simulated plasma box [ Note : the previous files can be opened as follows import numpy as np vector_file_name = np.load('file_name.npz') # Use these for the .npz files characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1) ] ------------------------------------------------------------------------------------------------------- Characteristics of the simulated plasma box (TEST_Luca.dat) nx        :    amount of spatial grid points xl        :    physical size of the spatial box, expressed in Debye length tt_w        :    time resolution for ion and electron density, electric field, electric potential and charge rap_m          :    ion-to-electron mass ratio R_p        :    ion-to-electron temperature ratio dt        :    time step used to evolve in time the numerical simulation emission    :    emission frequency power        :    amplitude of the electric charge imposed at the emitting antennas (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional     functionalities of the model. For the use of this dataset, they can be discarded.)

opencc-by-4.0May 2023View details →

Large Scale Travelling Ionospheric Disturbances during geomagnetic storms of 17 March and 23 June 2015 in the Australian region

This repository contains compilation of data in .mat (Matlab) format used in this work. Raw foF2 data e.g., in Data15-20Mar2015.mat has the format [Month, Day, Hour, Minute, foF2]. These are provided for each site of the network under the URSI station code.  Residuals data e.g., in Residuals_15_20Mar2015.mat contains fof2 perturbations after removing daily trends and outliers and have been upscaled to 1 minute intervals. Note: y11 - Brisbane,  y22 - Canberra, y33 - Camden, y44 - Hobart, y55 - Norfolk, y66 - Townsville, y77 - Darwin, and time is in seconds. Dst and AE data (AE_DST_struct_files.mat) is contained in a structure array with Dst in field 1 and AE in field 2.  IMF Bz data (IMF_Bz_LSTID_Paper.mat) has the format [Year DOY Hour Value].

opencc-by-4.0Aug 2023View details →

Community Detection to Split Large-scale Assemblies in Subassemblies

The motivation for the preprocessing of large-scale CAD models for assembly-by-disassembly approaches. The assembly-by-disassembly is only suitable for assemblies with a small number of parts (n_{parts} < 22). However, when dealing with large-scale products with high complexity, the CAD models may not contain feasible subassemblies (e.g. with connected and interference-free parts) and have too many parts to be processed with assembly-by-disassembly. Product designers' preferences during the design phase might not be ideal for assembly-by-disassembly processing because they do not consider subassembly feasibility and the number of parts per subassembly concisely. An automated preprocessing approach is proposed to address this issue by splitting the model into manageable partitions using community detection. This will allow for parallelised, efficient and accurate assembly-by-disassembly of large-scale CAD models. However, applying community detection methods for automatically splitting CAD models into smaller subassemblies is a new concept and research on the suitability for ASP needs to be conducted. Therefore, the following underlying research question will be answered in this experiments: Underlying research question 2: Can automated preprocessing increase the suitability of CAD-based assembly-by-disassembly for large-scale products? A hypothesis is formulated to answer this research question, which will be utilised to design experiments for hypothesis testing. Hypothesis 2: Community detection algorithms can be applied to automatically split large-scale assemblies in suitable candidates for CAD-based AND/OR graph generation.}

opencc-by-4.0Aug 2023View details →

Simulations for impacts of large-scale Saharan solar farms on the global terrestrial carbon cycle

Four experiments were conducted to investigate the impact of a large scale Saharan solar farm on the global carbon cycle. Here a fully coupled Earth System model (ESM) EC-Earth was used to investigate the impact of a Saharan solar farm on the terrestrial carbon cycle, simulated with prescribed reduced surface albedo approximating the albedo effect of Photovoltaic (PV) solar panels over the Sahara desert. These experiments considered solar panel coverage at 5, 20 or 50% of a region of the Sahara Desert.  The dataset contains selected output data from the simulations. Simulations were run for 200 years. The last 60 years were used for analysis after the model reached an equilibrium.  The dataset contains Earth system model results from EC-Earth3 presented in the study by Power et al. (2023).